WRANGLERS
Photo by Snehal Krishna on Unsplash
Remember, it is never the knife’s fault…
— Daniel Boulud
df = read.csv("archetypes/knife-crime/knife-crime.csv", header = TRUE, stringsAsFactors = TRUE)
df
df_rising <- filter(df, color == "Increase in knife crimes")
df_declining <- filter(df, color == "Decrease in knife crimes")
theme_opts <- theme(
panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.minor.y = element_blank(),
axis.ticks = element_line(),
legend.position = "none"
)
v1 = ggplot(df_rising) +
geom_point(aes(x=X2017, y=factor(Area.Name)), shape=16, alpha=1.0, size=2, color="#a82e13") +
geom_segment(aes(x=X2017, y=factor(Area.Name), xend=X2018, yend=factor(Area.Name)),
lineend = "round", linejoin = "round", size=1, color="#a82e13") +
geom_text(aes(x=X2018, y=Area.Name), label = "\u25B6", size = 12, color="#a82e13", vjust = 0.55) +
scale_x_continuous() +
scale_y_discrete() +
labs(title = "Where is knife crime rising?") +
theme_minimal() +
theme_opts +
xlab(NULL) +
ylab(NULL)
girafe(ggobj = v1, width_svg = 1280/72, height_svg = 720/72,
options = list(opts_sizing(rescale = TRUE, width = 1.0)))
v2 = ggplot(df_declining) +
geom_point(aes(x=X2017, y=factor(Area.Name)), shape=16, alpha=1.0, size=2, color="#63a0cd") +
geom_segment(aes(x=X2017, y=factor(Area.Name), xend=X2018, yend=factor(Area.Name)), size=1, color="#63a0cd") +
geom_text(aes(x=X2018, y=Area.Name), label = "\u25C0", size = 12, color="#63a0cd", vjust = 0.55) +
scale_x_continuous() +
scale_y_discrete() +
labs(title = "Where is knife crime decreasing?") +
theme_minimal() +
theme_opts +
xlab(NULL) +
ylab(NULL)
girafe(ggobj = v2, width_svg = 1280/72, height_svg = 720/72,
options = list(opts_sizing(rescale = TRUE, width = 1.0)))
Inspiration: Datawrapper, Where is knife crime rising?, https://blog.datawrapper.de/weekly-chart-range-plot-the-times-ryan-watts/ Data Source: Office for National Statistics